How the value of the environment controls persistence in visual search

PLoS Comput Biol. 2021 Dec 14;17(12):e1009662. doi: 10.1371/journal.pcbi.1009662. eCollection 2021 Dec.


Classic foraging theory predicts that humans and animals aim to gain maximum reward per unit time. However, in standard instrumental conditioning tasks individuals adopt an apparently suboptimal strategy: they respond slowly when the expected value is low. This reward-related bias is often explained as reduced motivation in response to low rewards. Here we present evidence this behavior is associated with a complementary increased motivation to search the environment for alternatives. We trained monkeys to search for reward-related visual targets in environments with different values. We found that the reward-related bias scaled with environment value, was consistent with persistent searching after the target was already found, and was associated with increased exploratory gaze to objects in the environment. A novel computational model of foraging suggests that this search strategy could be adaptive in naturalistic settings where both environments and the objects within them provide partial information about hidden, uncertain rewards.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Animals
  • Appetitive Behavior / physiology*
  • Choice Behavior / physiology*
  • Computational Biology
  • Conditioning, Operant / physiology
  • Environment*
  • Macaca mulatta
  • Male
  • Models, Psychological
  • Motivation
  • Reward*
  • Visual Fields / physiology*